Understanding the sample size is crucial when interpreting statistical data. A 50% complication rate may seem alarming; however, if this rate is derived from a small sample, it may not be statistically significant or representative of the broader population. Larger sample sizes generally provide more reliable estimates of true complication rates. Therefore, knowing the sample size helps assess the validity and reliability of the data presented.
[References:, NAHQ CPHQ Exam Preparation Materials: Health Data Analytics, NAHQ Body of Knowledge: Health Data Analytics, , , , , ]
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